Using data to drive innovation

In recent years, we’ve been on a journey that is challenging the way we view and use data. It’s a journey that has started to fundamentally change the way we think and act as an organisation.

It’s easy to view advances in technology and information as a way of just making existing transactional processes more efficient. However, a focus solely on efficiency, as important as that is, can prevent you from identifying more transformational opportunities.

At AFSA, we are committed to delivering the right services to the right people in the right way, to support compliant behaviour and early identification of bad behaviour. Capturing the right data in a form that supports quality data analytics is one of the keys to success.

For us the first step has been to build organisational awareness that data is central to organisational success. This starts with building an understanding of the value of data as an asset. We have worked to do this by building a systems-orientated view of our organisation’s role and purpose, which has enabled our staff to see the complementary relationship between the data they collect and use, across functional and divisional boundaries. This has provided us with insights that help us to curate our data holdings—so they can be enriched and used to develop analytical models that guide decision-making and innovation.

This is when momentum really starts to build, as it energises people to look for other opportunities to use data to inform operational and strategic decisions. Capitalising on this requires having the right skills and expertise in place to respond to the demand, as well as close engagement between the analysts and business.

At AFSA we’ve used our analytics capability to develop econometric modelling that supports decision-making by our National Management Board. For us this has involved building a better understanding of the correlations between various economic indicators, which we can then use to forecast personal insolvencies. Our governance bodies discuss and test the underlying forecasts and assumptions and overlay that with environmental scanning to identify emerging issues that can be brought back into the model.

These econometric models have been important in supporting decision-making around resourcing and funding, as AFSA operates on a cost-recovery basis. It also provides us with confidence that these relationships will hold over time and are not due to chance.

We are using data to shape our regulatory approach. As a regulator, we have always valued market intelligence, however in the past we’ve relied on market intelligence, experience and limited use of data. We knew we needed to change our approach to become data-driven supplemented by qualitative insights. Our analysis area worked with our regulators to design quantitative measures of these insights, as well as new measures from the wide range of data available both internally and externally. An algorithm brings these measures together to assess the risk of non-compliance of members of the regulated population. Regulation activities are now informed by live data that is adaptable to changing conditions.

As an organisation we recognise that we are at risk of missing opportunities that data offers, due to competing priorities or not having the time to invest in seizing every opportunity that comes past. This is why supporting events like GovHack is important to us as it asks the broader community to use data in innovative ways to solve problems facing the public sector. Most recently, we asked participants to consider how we might identify those who may break the laws that we administer, to help us direct our resources to both education and enforcement activities.

We engaged the winning team to work with us to implement their ideas. This is being used in conjunction with our work to identify and better understand our clients, for example through the use of personas based on data, to inform service delivery.

We are committed to supporting academic research in areas that are relevant to our work. Providing a confidentialised micro-data file for major research by the University of Melbourne’s Law School, provided new insights and led us to adopt recommendations on the way we collect some of our data.

Data is not limited to tracking outputs from transactional processes. It is vital in supporting informed thinking and decisions. Here are what I see as the key steps to consider when embarking on a similar journey:

  1. Consider how your organisation has deployed technology. Look at how data is being used to inform thinking and decisions—if it’s only being used to track outputs from transactional processes, the potential value of your data will not be fully appreciated.
  2. Encourage your staff to think about the data they use and collect from a system’s perspective rather than a functional one.
  3. Use the insights gained to curate data and enrich it with other data to support data analytics.
  4. Develop your data analytics capability so you can quickly show how data can be used in ways that provide insights and will support better organisational decision making. This is critical to build momentum and mature data analytics as an embedded part of day to day operations.

This approach has enabled us to use data to guide a number of corporate, regulatory and service delivery decisions and initiatives. However, as our awareness of the value of data grows we are realising there are so many more opportunities. With the rapid speed of change and transformation, our destination is constantly evolving, and our journey is evolving with it.